{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 准备数据集\n",
    "# 用np生成一些序列数据，这个序列数据有四段\n",
    "def waveform_dataset(points_num):\n",
    "    '''建立波形数据集，这个数据集含有四段，每一段的数据点数为points_num'''\n",
    "    stage1=1*np.cos(np.arange(points_num))\n",
    "    stage2=2*np.cos(np.arange(points_num))\n",
    "    stage3=3*np.cos(np.arange(points_num))\n",
    "    stage4=4*np.cos(np.arange(points_num))\n",
    "    \n",
    "    dataset_X=np.array([stage1,stage2,stage3,stage4])# 4行points_num列\n",
    "    dataset_X=dataset_X.reshape(points_num*4,1) # 转变为：4*points_num行，一列，即为整个序列\n",
    "    \n",
    "    amp1 = np.ones(points_num) # 每一段数据的幅度不同 分别是1,4,2,0.5\n",
    "    amp2 = 4 + np.zeros(points_num) \n",
    "    amp3 = 2 * np.ones(points_num) \n",
    "    amp4 = 0.5 + np.zeros(points_num) \n",
    "    dataset_y=np.array([amp1,amp2,amp3,amp4]).reshape(points_num*4,1)\n",
    "    return dataset_X,dataset_y\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18ab7e80>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 查看时序数据集\n",
    "dataset_X,dataset_y=waveform_dataset(50)\n",
    "plt.plot(dataset_X)\n",
    "plt.plot(dataset_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 300; Error: 0.08632353521527447;\n",
      "Epoch: 600; Error: 0.07758197978278435;\n",
      "Epoch: 900; Error: 0.047083147244329486;\n",
      "Epoch: 1200; Error: 0.03948011155907889;\n",
      "Epoch: 1500; Error: 0.03808612642771739;\n",
      "Epoch: 1800; Error: 0.03600983543384789;\n",
      "Epoch: 2100; Error: 0.04108011778013388;\n",
      "Epoch: 2400; Error: 0.0388262030539809;\n",
      "Epoch: 2700; Error: 0.033576743782171244;\n",
      "Epoch: 3000; Error: 0.03329548827926802;\n",
      "The maximum number of train epochs is reached\n"
     ]
    }
   ],
   "source": [
    "# 构建并训练模型\n",
    "import neurolab as nl\n",
    "net = nl.net.newelm([[-2, 2]], [10, 1], [nl.trans.TanSig(), nl.trans.PureLin()])\n",
    "# 创建两层的神经网络\n",
    "net.layers[0].initf = nl.init.InitRand([-0.1, 0.1], 'wb')\n",
    "net.layers[1].initf= nl.init.InitRand([-0.1, 0.1], 'wb')\n",
    "net.init()\n",
    "# 网络的初始化\n",
    "error = net.train(dataset_X, dataset_y, epochs=3000, show=300, goal=0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Comparison of Truth and Predicted')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 用训练好的模型预测新样本\n",
    "predict_y=net.sim(dataset_X)\n",
    "plt.plot(dataset_y,label='dataset')\n",
    "plt.plot(predict_y,label='predicted')\n",
    "plt.legend()\n",
    "plt.title('Comparison of Truth and Predicted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Comparison of Truth and Predicted')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 生成新的数据集\n",
    "newset_X,newset_y=waveform_dataset(100)\n",
    "predict_y=net.sim(newset_X)\n",
    "plt.plot(newset_y,label='dataset')\n",
    "plt.plot(predict_y,label='predicted')\n",
    "plt.legend()\n",
    "plt.title('Comparison of Truth and Predicted')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
